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GitHub Configuration

GitHub Configuration

Un servidor de Protocolo de Contexto de Modelo (MCP) para la aplicación de gestión de tareas TickTick.

makefilemcpserver

makefilemcpserver

An MCP server that exposes Makefile targets as callable tools for AI assistants, allowing Claude and similar models to execute Make commands with provided arguments.

RobotFrameworkLibrary-to-MCP

RobotFrameworkLibrary-to-MCP

Okay, I can help you understand how to turn a Robot Framework library into an MCP (Message Center Protocol) server. It's a bit of a complex process, but here's a breakdown of the concepts and steps involved, along with considerations: **Understanding the Goal** First, let's clarify what we mean by "turning a Robot Framework library into an MCP server." Essentially, you want to expose the functionality of your Robot Framework library so that other applications (clients) can access and use it remotely via the MCP protocol. **Key Concepts** * **Robot Framework Library:** A collection of keywords (functions) that can be used in Robot Framework test cases. * **MCP (Message Center Protocol):** A communication protocol used for exchanging messages between applications. It's often used in embedded systems and other scenarios where a lightweight, reliable communication mechanism is needed. It defines how messages are formatted, sent, and received. * **Server:** A program that listens for incoming requests from clients and provides services in response. In this case, the server will receive MCP messages, interpret them as requests to execute Robot Framework library keywords, and send back the results as MCP messages. * **Client:** A program that sends requests to the server. **General Steps** Here's a high-level outline of the steps involved: 1. **Choose an MCP Implementation/Library:** You'll need a library or framework that handles the MCP protocol details (message encoding/decoding, connection management, etc.). There isn't a single, universally standard MCP library, so you'll need to find one that suits your needs and programming language. If you're using Python (which is common with Robot Framework), you might need to adapt an existing MCP implementation or create your own. 2. **Create a Server Application:** This will be the core of your MCP server. It will: * **Listen for Incoming Connections:** Set up a socket to listen for incoming TCP/IP connections from MCP clients. * **Receive MCP Messages:** Receive and decode MCP messages from clients. * **Parse MCP Messages:** Determine which Robot Framework keyword the client is requesting to execute and extract any arguments. * **Execute Robot Framework Keywords:** Call the appropriate keyword from your Robot Framework library with the provided arguments. * **Format Results as MCP Messages:** Take the results returned by the Robot Framework keyword (success/failure, return values) and encode them into MCP messages. * **Send MCP Response:** Send the MCP response message back to the client. * **Handle Errors:** Gracefully handle errors that occur during message processing or keyword execution. 3. **Map MCP Messages to Robot Framework Keywords:** You'll need a mechanism to map incoming MCP messages to specific keywords in your Robot Framework library. This could be a simple lookup table or a more sophisticated routing system. 4. **Implement Data Serialization/Deserialization:** MCP messages are typically byte streams. You'll need to serialize data (arguments to keywords, return values) into a format suitable for transmission over MCP and deserialize it on the receiving end. Common serialization formats include: * **JSON:** Human-readable and widely supported. * **Protocol Buffers (protobuf):** Efficient and language-neutral. * **MessagePack:** Another efficient binary serialization format. * **Custom Binary Format:** If you need maximum performance or have very specific requirements, you could define your own binary format. 5. **Error Handling:** Implement robust error handling to catch exceptions during keyword execution, message parsing, or network communication. Send appropriate error messages back to the client via MCP. **Example (Conceptual - Python)** ```python # This is a simplified example and requires a real MCP library # and proper error handling. import socket import json from robot.api import logger # For Robot Framework logging # Assume you have a Robot Framework library called 'MyLibrary' from MyLibrary import MyLibrary # MCP Configuration HOST = '127.0.0.1' # Standard loopback interface address (localhost) PORT = 65432 # Port to listen on (non-privileged ports are > 1023) # Initialize Robot Framework library my_library = MyLibrary() def handle_client(conn, addr): print(f"Connected by {addr}") while True: data = conn.recv(1024) # Receive data from the client if not data: break try: # Decode MCP message (assuming JSON for simplicity) message = json.loads(data.decode('utf-8')) keyword = message['keyword'] args = message.get('args', []) # Arguments are optional # Execute Robot Framework keyword try: result = getattr(my_library, keyword)(*args) # Call the keyword response = {'status': 'success', 'result': result} except Exception as e: logger.error(f"Error executing keyword: {e}") response = {'status': 'error', 'message': str(e)} # Encode response as MCP message (JSON) response_data = json.dumps(response).encode('utf-8') conn.sendall(response_data) except json.JSONDecodeError: error_message = {'status': 'error', 'message': 'Invalid JSON'} conn.sendall(json.dumps(error_message).encode('utf-8')) except AttributeError: error_message = {'status': 'error', 'message': f'Keyword "{keyword}" not found'} conn.sendall(json.dumps(error_message).encode('utf-8')) except Exception as e: logger.exception("Unexpected error") error_message = {'status': 'error', 'message': f'Internal server error: {e}'} conn.sendall(json.dumps(error_message).encode('utf-8')) conn.close() print(f"Connection closed with {addr}") def start_server(): with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((HOST, PORT)) s.listen() print(f"Listening on {HOST}:{PORT}") while True: conn, addr = s.accept() handle_client(conn, addr) # Handle each client in a separate thread for concurrency (recommended) if __name__ == "__main__": start_server() ``` **Important Considerations** * **Security:** If you're exposing your Robot Framework library over a network, security is paramount. Consider: * **Authentication:** Verify the identity of clients before allowing them to execute keywords. * **Authorization:** Control which clients have access to which keywords. * **Encryption:** Encrypt the MCP messages to protect sensitive data in transit (e.g., using TLS/SSL). * **Concurrency:** If you expect multiple clients to connect to your server simultaneously, you'll need to handle concurrency properly (e.g., using threads or asynchronous programming). The example above shows a basic single-threaded server. For production, you'd want to use threads or asyncio. * **Error Handling:** Implement robust error handling to catch exceptions during keyword execution, message parsing, or network communication. Send appropriate error messages back to the client via MCP. * **Data Types:** Carefully consider how you'll handle data types when passing arguments to keywords and returning results. MCP typically deals with byte streams, so you'll need to serialize and deserialize data appropriately. * **Performance:** If performance is critical, choose efficient serialization formats and optimize your code. * **MCP Library Choice:** The choice of MCP library will significantly impact the complexity of your implementation. If a suitable library doesn't exist, you might need to implement the MCP protocol yourself, which is a non-trivial task. **In summary:** Turning a Robot Framework library into an MCP server involves creating a server application that listens for MCP messages, parses them to determine which Robot Framework keyword to execute, executes the keyword, and sends the results back to the client as MCP messages. You'll need to choose an MCP library, implement data serialization/deserialization, and handle concurrency and security. The complexity of the task depends on the specific requirements of your application and the availability of suitable MCP libraries. The example code provides a basic starting point, but it needs to be adapted and extended to meet the needs of a real-world application. Remember to prioritize security and error handling.

MCP Bridge API

MCP Bridge API

MCP Bridge es un proxy ligero, rápido y agnóstico a LLM para conectarse a múltiples servidores del Protocolo de Contexto de Modelos (MCP) a través de una API REST unificada. Permite la ejecución segura de herramientas en diversos entornos como dispositivos móviles, web y periféricos. Diseñado para la flexibilidad, la escalabilidad y la fácil integración con cualquier backend de LLM.

ITSM Integration Platform

ITSM Integration Platform

Here are a few possible translations of "MCP for ITSM tool integration," depending on the context. "MCP" is the tricky part, as it could stand for several things. I'll provide options based on the most likely interpretations: **Assuming "MCP" stands for "Managed Cloud Provider":** * **Integración de herramientas ITSM con un proveedor de nube gestionada.** (This is a general translation.) * **Integración de herramientas ITSM a través de un proveedor de nube gestionada.** (This emphasizes the "through" aspect.) **Assuming "MCP" stands for "Microsoft Certified Professional" (less likely in this context, but possible):** * **Integración de herramientas ITSM con un profesional certificado de Microsoft.** (This is a literal translation, but might not be the best if you're talking about a *solution* rather than a person.) * **Integración de herramientas ITSM con una solución basada en la certificación Microsoft.** (This is a more nuanced translation, suggesting the integration leverages Microsoft certification standards.) **Assuming "MCP" is an acronym specific to the company or project:** * **Integración de herramientas ITSM con [Nombre completo de MCP].** (The best option if you know what MCP stands for. For example: "Integración de herramientas ITSM con el Módulo de Control de Procesos.") **General Options (if you don't know what MCP stands for and need a placeholder):** * **Integración de herramientas ITSM con MCP.** (Simply leaves the acronym as is. This is fine if the audience knows what MCP means.) * **Integración de herramientas ITSM con [Sistema/Plataforma/Herramienta] MCP.** (This is a more descriptive placeholder, suggesting what MCP *might* be.) **Therefore, to give you the *best* translation, I need to know what "MCP" stands for in your context.** Please provide more information!

Macroforge MCP Server

Macroforge MCP Server

Enables AI assistants to access Macroforge documentation, validate TypeScript code with @derive decorators, expand macros, and retrieve macro documentation.

OpenFeature MCP Server

OpenFeature MCP Server

Provides OpenFeature SDK installation guidance through MCP tool calls. Enables AI clients to fetch installation prompts and setup instructions for various OpenFeature SDKs across different programming languages and frameworks.

Mcp Server Basic Sample

Mcp Server Basic Sample

REMnux Documentation MCP Server

REMnux Documentation MCP Server

Enables AI assistants to search and retrieve information from the REMnux malware analysis toolkit documentation, allowing users to ask questions about reverse-engineering tools and get accurate, up-to-date answers from the live documentation.

Fusion 360 MCP Integration

Fusion 360 MCP Integration

Enables AI assistants to interact programmatically with Autodesk Fusion 360 for creating parametric 3D models through simple API calls.

InstantDB MCP Server

InstantDB MCP Server

A read-only interface for querying InstantDB that dynamically loads schemas and enables executing queries through pre-defined patterns.

Apifox MCP

Apifox MCP

Enables AI assistants to automatically manage Apifox API documentation by importing OpenAPI/Swagger specifications and exporting existing API structures. Supports batch operations, intelligent deprecation marking, and smart scope detection for partial module imports.

Financial Data MCP Server

Financial Data MCP Server

A Model Context Protocol server that provides financial tools for retrieving real-time stock data, analyst recommendations, financial statements, and web search capabilities for a LangGraph-powered ReAct agent.

Cursor n8n Builder

Cursor n8n Builder

Enables AI assistants in Cursor IDE to manage n8n workflows through the n8n REST API, including creating, updating, activating workflows, viewing execution history, and triggering webhooks.

Loop MCP Server

Loop MCP Server

Enables LLMs to process arrays item-by-item or in batches with a specific task, storing and retrieving results with optional summarization after completion.

PostgreSQL MCP Server

PostgreSQL MCP Server

Enables interaction with PostgreSQL databases through both HTTP and stdio transports. Supports executing read-only SQL queries, listing tables, and retrieving schema information with stateful session management.

Python Server MCP

Python Server MCP

Un servicio de precios de criptomonedas que proporciona información de precios de criptomonedas en tiempo real a través de un marco MCP (Protocolo de Contexto de Modelo) con integración de la API de CoinMarketCap.

TOPdesk MCP Server

TOPdesk MCP Server

Enables interaction with TOPdesk service management platform through comprehensive API integration. Supports incident management, operator/person operations, document conversion, and FIQL querying for streamlined IT service desk workflows.

Obsidian MCP Server

Obsidian MCP Server

Connects AI assistants directly to Obsidian vaults with intelligent note creation using templates, semantic search, smart tagging to avoid duplicates, and specialized agent roles (Guardian, Researcher, Connection Weaver) for managing knowledge bases.

mcp-server

mcp-server

MCP Server TypeScript Starter

MCP Server TypeScript Starter

A Model Context Protocol (MCP) server that provides location services

PostgreSQL Model Context Protocol (PG-MCP) Server

PostgreSQL Model Context Protocol (PG-MCP) Server

Google Docs MCP Server

Google Docs MCP Server

Enables Claude to read, create, and update Google Docs through OAuth authentication. Deployed as a remote Next.js server on Vercel with support for multiple users and secure API key management.

Jinko

Jinko

Jinko

Kali MCP Server

Kali MCP Server

Provides a containerized Kali Linux environment that gives AI assistants access to a comprehensive suite of security and penetration testing tools. It enables automated vulnerability scanning, network reconnaissance, and secure command execution through the Model Context Protocol.

Instagram DM MCP Server

Instagram DM MCP Server

Enables sending and receiving Instagram Direct Messages, managing conversations, downloading media, viewing user profiles and stories, and interacting with posts through natural language in Claude.

Ixnetwork Mcp

Ixnetwork Mcp

Servidor MCP para la gestión de sesiones de IxNetwork.

A2AMCP

A2AMCP

A Redis-backed MCP server that enables multiple AI agents to communicate, coordinate, and collaborate while working on parallel development tasks, preventing conflicts in shared codebases.

Anki MCP Server

Anki MCP Server

Enables interaction with the Anki desktop app for spaced repetition learning. Supports reviewing due cards, creating new flashcards, and managing study sessions through natural language commands.

w3c-mcp

w3c-mcp

MCP Server for accessing W3C/WHATWG/IETF web specifications. Provides AI assistants with access to official web standards data including specifications, WebIDL definitions, CSS properties, and HTML elements.